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Frame rate up-conversion algorithm based on adaptive-agent motion compensation combined with semantic feature analysis

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Abstract

In this paper, a novel video frame rate up-conversion (FRUC) technique based on adaptive motion compensation is presented by combining the semantic feature analysis for image sequences. Firstly, the image is divided into the sub-patch with the same size and their feature areextracted. And, semantic feature analysis is adopted to generate a more accurate motion vector field from the previous frame to the following frame, and then we select these suitable classification algorithms for patial-temporal patches to divide the frame into moving areas, static areas and fault areas. By using the semantic-based adaptive interpolation, we developed a hierarchical refinement strategy to adaptively correct these motion vector so as to get the interpolation frame. Experimental results show that the performance of our method is better than those of the popular I-FRUC, B-FRUC, F-FRUC and A-FRUC methods in both objective and subjective quality, which has relative advantage for engineering applications.

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Authors and Affiliations

  1. College of Computer Science, Yangtze University, Jingzhou, 434000, Hubei, China

    Guorui Chen

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  1. Guorui Chen
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Correspondence to Guorui Chen.

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Chen, G. Frame rate up-conversion algorithm based on adaptive-agent motion compensation combined with semantic feature analysis. J Ambient Intell Human Comput 11, 511–518 (2020). https://doi.org/10.1007/s12652-018-0974-1

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  • DOI: https://doi.org/10.1007/s12652-018-0974-1

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